Early Warning between 30 to 90 days
Data has to be checked every month to prevent any of the cases mentioned. Early detection will prevent massive loss, which could be irreversible after it makes it to P&L. As a best practice CFO must review any abnormality. Humans cannot identify as its AI / ML reading signals from data set.
What do executives from manufacturing look for?
Where Are We Losing Money on the Shop Floor Right Now?
Why executives care:
Most manufacturing losses never hit a single line item — they hide in scrap, rework, and micro-stoppages.
Data insight answers:
Which lines, machines, or shifts generate the highest scrap or rework
Where OEE is declining and why
Which products erode margin despite good sales
Who cares most: CEO, CFO, COO
Executive thought: “Show me where profit is leaking today.”
What Is Most Likely to Fail or Go Down Next?
Why executives care:
Unplanned downtime destroys schedules, revenue, and customer trust.
Data insight answers:
Which machines show abnormal vibration, cycle time, or defect trends
Where maintenance is reactive instead of predictive
Which failures repeat without root cause resolution
Who cares most: COO, Plant Manager, CIO
Executive thought: “What will stop production next?”
Which Decisions Are Driving Cost Without Improving Output?
Why executives care:
Manufacturers often spend more but produce the same — or worse.
Data insight answers:
Why labor, energy, or overtime costs are rising
Which suppliers or materials increase defect rates
Where process changes created hidden inefficiencies
Who cares most: CFO, COO, Procurement
Executive thought: “Why are costs up but output flat?”
What Happens If We Don’t Fix This in the Next 90 Days?
Why executives care:
Manufacturing risk compounds quickly — missed deliveries turn into lost contracts.
Data insight answers:
Which trends will worsen scrap, downtime, or delays
Where capacity constraints will impact revenue
Which customers or SLAs are at risk
Who cares most: CEO, Board
Executive thought: “What problem is about to get bigger?”